Hourly data analytics widget allows data analysts to compare the selected entity across the same metric at the same period by hour.

When a dataset is selected, some default value will be set and render the basic widget. Data analysts may update the selectors accordingly to achieve the desired analysis.

Introduction

[1] Entity

The entity list will display all available sites / site groups / areas / area groups based on the dataset and granularity selected. You may select the desired entity or select all in a group for comparison

[2] Metric

The metric available will be dependent on the dataset selected. Kindly refer here for the full list of dataset available.

[3] Period

The time series period is ready with relative date range and compared period.

Relative Date Range

Relative date range is dynamic time interval in relation with today, for our system, we ready with compare period of preceding period and preceding year.

Type	Current Period	Compared Period
Day	Today Yesterday	Preceding day Same day last week Same day last year
Week	Last 7 days including today This week Last week	Preceding period Preceding year
Month	Last 30 days including today This month Last month	Preceding period Preceding year
Custom	Custom date range	Custom date range

Data analysts may choose to show the data as a total or average number, and also separate them into weekday or weekend to have better insights. 

Hourly data analytics widget also comes with bar chart display mode, data analysts may change the chart type using the toggle at the top left corner.

Restriction

To ensure optimal performance and prevent data processing delays, the Hourly Data Analytics widget has a maximum query limit of 50,000 records.

Important Information:

• Partial Results: When the maximum query limit is reached, the data displayed will only be a partial result set. This means that the chart may not show all possible data points for the selected query.
• Recommendation: To obtain complete and accurate data, please adjust your query parameters by:
  • Selecting a shorter date range.
  • Reducing the number of entities.
  • Limiting the metrics included in the query.